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of the Center for integrative neuroplasticity (CINPLA) and in the INTED center. This PhD project will focus on reinforcement learning methods for generating complex structures with two possible application areas
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machine learning (ML) methods are widely used to explore structure in complex and high-dimensional data, particularly in the life sciences, where clustering analyses often form the basis for biological
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surfaces and when actively driving a soft sheet near a wall. Essential to the projects is developing a new understanding of the fluid-structure interactions, that is to say, the coupling between hair’s
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the neuroscience work package which will investigate how HC use during adolescence influences structural and functional brain development and depression risk. Adolescence is a critical period of brain maturation and
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for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows
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. Place of work is Department of Informatics at Blindern, Oslo. Job description Unsupervised machine learning (ML) methods are widely used to explore structure in complex and high-dimensional data
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project will focus on reinforcement learning methods for generating complex structures with two possible application areas (i) the generation of virus capsids for gene therapy and (ii) the generation
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Website https://karriere.norceresearch.no/en/jobs/7235739-phd-research-fellow-in-data-a… Requirements Research FieldMathematics » Applied mathematicsEducation LevelMaster Degree or equivalent Skills
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Experience or competence in heterologous production of enzymes is an advantage Teaching experience is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good
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. The research group has an excellent infrastructure, MiNaLab, covering chemical, structural, optical and electrical characterization methods, material growth, device fabrication and simulations. The student will